Instructions to use chitandaumen/api-malware_classificationv1.3_seq4096 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chitandaumen/api-malware_classificationv1.3_seq4096 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="chitandaumen/api-malware_classificationv1.3_seq4096")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("chitandaumen/api-malware_classificationv1.3_seq4096") model = AutoModelForSequenceClassification.from_pretrained("chitandaumen/api-malware_classificationv1.3_seq4096", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f184819e0a7f68f4049686ab94d53ee52f0dd0db032598cfc49f1ed1ac727eef
- Size of remote file:
- 517 MB
- SHA256:
- 22550f56d3928e5dd1e6fab7e86e4d73ed1d7cc5c17925f8b7804ab023a581c1
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